Land fragmentation in southern Ontario: A tragedy of the spatial anticommons
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Competition between agricultural operations, urban transplants, and ecological interests is changing the nature of property rights and land use in rural Ontario. In a region with valuable ecosystems and climate, soil, and location traditionally well-suited for crop and livestock production, plot sizes are decreasing as land is subdivided and allocated to non-agricultural residential use. Although this practice can increase property value for farmers, Michael Heller’s spatial anticommons may also be observed, such that “each owner receives a core bundle of rights, but in too small a space for the most efficient use” [2]. The purpose of this paper is to introduce a new application of Heller’s anticommons theory, examining how the increasingly patchwork-like distribution of rural land parcels can be expected to affect farm and ecosystem productivity. Ultimately, deadweight loss occurs because neither agricultural nor ecological economies of scale can be recognized on plots that are too small for efficient use. Using rural planning reports and habitat ecology studies, trends in the fragmentation process are described and compared to the aims of provincial land-use policy, including the Provincial Policy Statement, the Greenbelt Act, and the Places to Grow Act. While the goals of farmers and conservationists may at times seem discrete or incompatible, the anticommons framework may be used to identify shared challenges. Thus the two parties might consider how collective action could be used to overcome the difficulties of reuniting subdivided tracts of land.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it